Symmetric Alternating Direction Method with Indefinite Proximal Regularization for Linearly Constrained Convex Optimization

Symmetric Alternating Direction Method with Indefinite Proximal Regularization for Linearly Constrained Convex Optimization
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线性约束凸优化的不定近端正则化对称交替方向法

DOI:
10.1007/s10957-017-1207-z
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发表时间:
2017-12
影响因子:
1.9
通讯作者:
Ma Feng
Ma Feng
中科院分区:
数学3区
文献类型:
--
作者:
Gao Bin;Ma Feng

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乘子交替方向近似法是求解线性约束可分凸问题的一种常用方法,特别是线性化情形。在文献中,在近似正则化矩阵是半正定的假设下,近似交替方向法的收敛性已经被建立。最近,它表明,在最近的交替方向乘子方法的正则化最近的条款不一定是半正定的,没有任何额外的假设。然而,它仍然是未知的不确定的设置是否是有效的对称交替方向法的乘数的近端版本。在本文中,我们确认,对称交替方向法的乘子也可以正则化与一个不定的邻近项。我们从理论上证明了不定方法的全局收敛性,并在遍历意义下建立了其最坏情况下的收敛速度。另外,Eckstein和Bertsekas提出的广义交替方向乘子法是本文讨论的特例。最后,我们通过实验结果证明了使用不定近端项时所取得的性能改进。
The proximal alternating direction method of multipliers is a popular and useful method for linearly constrained, separable convex problems, especially for the linearized case. In the literature, convergence of the proximal alternating direction method has been established under the assumption that the proximal regularization matrix is positive semi-definite. Recently, it was shown that the regularizing proximal term in the proximal alternating direction method of multipliers does not necessarily have to be positive semi-definite, without any additional assumptions. However, it remains unknown as to whether the indefinite setting is valid for the proximal version of the symmetric alternating direction method of multipliers. In this paper, we confirm that the symmetric alternating direction method of multipliers can also be regularized with an indefinite proximal term. We theoretically prove the global convergence of the indefinite method and establish its worst-case convergence rate in an ergodic sense. In addition, the generalized alternating direction method of multipliers proposed by Eckstein and Bertsekas is a special case in our discussion. Finally, we demonstrate the performance improvements achieved when using the indefinite proximal term through experimental results.
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